A Context Query Language for Pervasive Computing Environments

Reichle, Roland; Wagner, Michael; Khan, Mohammad Ullah; Geihs, Kurt; Valla, Massimo; Fra, Cristina; Paspallis, Nearchos; Papadopoulos, George Α.

doi:10.1109/percom.2008.29

Cited by 38 publications

(21 citation statements)

References 7 publications

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“…First of all, most of context models consider a given subject that is observed, typically the user. For instance, Reichle et al [17] and Najar et al [11] consider both that a given "entity" (the user, a device, etc.) is observed.…”

Section: Context Meta-modelmentioning

confidence: 99%

“…Around it, several elements can be considered. Reichle et al [17] call these observed elements "scope", while Kirsch-Pinheiro et al [9] call these "context elements". In both cases, it corresponds to what we really observe from the subject: its location (for a user), the available memory (for a device), etc.…”

Section: Context Meta-modelmentioning

confidence: 99%

“…Besides, some models associate meta-data describing these values. For instance, Reichle et al [17] propose to describe which representation is used for an observed value (e.g. a location can be described using latitude and longitude pair or through a postal address).…”

Section: Context Meta-modelmentioning

confidence: 99%

“…This way, event definition can take advantage of reasoning capabilities offered by ontologies. Besides, a context query language, such as [17], allows the expression of rich context conditions. This is particularly important since context information is naturally imprecise and often incomplete.…”

Section: Element(#hospital #Heating) = "Out Of Order" or Element(#homentioning

confidence: 99%

See 3 more Smart Citations

Dynamic Context Modeling for Agile Case Management

Kirsch-Pinheiro

Rychkova

2013

Lecture Notes in Computer Science

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Section: Context Meta-modelmentioning

confidence: 99%

Section: Context Meta-modelmentioning

confidence: 99%

Section: Context Meta-modelmentioning

confidence: 99%

Section: Element(#hospital #Heating) = "Out Of Order" or Element(#homentioning

confidence: 99%

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Dynamic Context Modeling for Agile Case Management

Kirsch-Pinheiro

Rychkova

2013

Lecture Notes in Computer Science

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“…The application developer just uses the generated getter-/setter-methods to access to data in the data structure. As part of our comprehensive approach for context modeling, reasoning and querying, we provide also an appropriate Context Query Language (CQL), which is described in Reichle et al [14] in more details. This CQL will also be used for the MDD as we can automatically generate the code corresponding to a static query.…”

Section: Model-driven Developmentmentioning

confidence: 99%

A Comprehensive Context Modeling Framework for Pervasive Computing Systems

Reichle

Wagner

Khan

et al. 2008

Lecture Notes in Computer Science

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Abstract. Context management in pervasive computing environments must reflect the specific characteristics of these environments, e.g. distribution, mobility, resource-constrained devices, or heterogeneity of context sources. Although a number of context models have been presented in the literature, none of them supports all of these requirements to a sufficient extent at the same time. In this paper, we present a comprehensive and integrated approach for context modeling in pervasive computing environments. It combines the advantages of existing approaches and addresses the need for supporting effective software development. The proposed context model follows an ontology-based approach and has three layers of abstraction, i.e. conceptual layer, exchange layer, and functional layer. This layered approach facilitates a model-driven development of context-aware applications. Throughout the paper we compare our solution with the related work in order to clearly demonstrate why we needed to develop a new context management framework and where we have adopted existing ideas.

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An MDD‐based method for building context‐aware applications with high reusability

Paspallis

2019

J Software Evolu Process

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Adding context -awareness capabilities to modern mobile and pervasive computing applications (apps) is becoming a mainstream activity in the software engineering community. In this respect, many context models and middleware architectures have been proposed with the aim to provide the developers with tools and abstractions that make it easier to produce context-aware applications. However, current solutions suffer from relatively low reusability and lack ease-of-use. In this paper, we propose a two-layer approach based on model-driven development: At the higher layer, we introduce the design of reusable context plug-ins, which can be used to monitor low-level context data and to infer higher-level information about the users, their computing infrastructure, and their interaction. At the lower layer, the plug-ins themselves are synthesized using more elementary, reusable components. We argue that this development approach provides significant advantages to the developers, as it enables them to design, implement, reuse, and maintain the codebase of context-aware apps more efficiently.To evaluate this approach, we demonstrate it in the context of a two-part example application and assess it both qualitatively and quantitatively. KEYWORDScode generation, context awareness, MDD, middleware, plug-in, reusability INTRODUCTIONContext awareness is one of the most sought-after features for modern mobile and pervasive computing applications. Understanding and using context allows applications to identify and predict intention, thus allowing for better and richer human-computer interaction.Researchers have proposed various approaches to ease the task of designing and implementing applications that are context-aware and self-adaptive. At their core, many of these build on reusable code, ranging from the early works of Dey 1 to more recent, plug-in-based architectures such as those described in the previous studies. 2-5 These approaches are designed to allow the applications, which are using them to inquire and access arbitrary context data types. In this respect, the context-awareness and context-inferring parts are separated from the functional logic of the applications by means of reusable context plug-ins (ie, individually deployable units, which provide mechanisms for collecting and processing context data, and inferring higher-level context information). At the same time, many context models and middleware architectures were proposed and documented in the literature. 6,7 Software reuse is at the core of many of those approaches. At a higher level, reuse covers all software engineering phases and ''can be supported by different types of methods, including ad hoc, opportunistic, adaptive, systematic, black-box, whitebox, etc.'' 8 A common drawback in these approaches is that the developers are required to invest a significant amount of time to develop customized components, which are used for collecting, processing, inferring, storing, querying, and accessing context data. Moreover, the developed components are then harder...

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A Context Query Language for Pervasive Computing Environments

Cited by 38 publications

References 7 publications

Dynamic Context Modeling for Agile Case Management

Dynamic Context Modeling for Agile Case Management

A Comprehensive Context Modeling Framework for Pervasive Computing Systems

An MDD‐based method for building context‐aware applications with high reusability

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